Description
Tech
- Regression modeling strategy
- we use a property to characterise a response within groups
- after specifying a regression structure, we optimize the model by some criteria
- AIC, BIC … for time-consuming models + large-scaled data
- AUROC, AUPRC … for prediction-focused + smaller-size data
- if assumptions are satisfied with the optimized model, we are allowed to do inference on estimated responce and effects.
- Longitudinal Data (serial data/repeated measures) Analysis
- Model-based
- General Least Squares (GLS)
- Mixed Effect Model
- Bayesian hierarchical models
- Data-based
Medical
- 4 primary groups
- non_pos: postive episodes from no-transplant patients
- non_neg: test-negative and baseline time windows from ‘pure negative’ no-transplant patients
- txp_pos: postive episodes from transplant patients
- txp_neg: test-negative and baseline time windows from ‘pure negative’ transplant patients
- An episode
- from 24 hours before to 24 hours after a blood stream acquisition
- Questions
- What’s the response trend of a feature during one ‘episode’ within groups?
- What’s the difference of response trend of a feature during one ‘episode’ across groups?
Report
- Assumption-satisfied Variables
- Temp
- Resp
- Pulse
- SBP
- DBP
- POTASSIUM
- ALBUMIN
- CALCIUM
- SODIUM
- WHITE_BLOOD_CELL_COUNT
- PHOSPHORUS
- PLATELET_COUNT
- CO2
- PCO2
- CHLORIDE
- BLOOD_UREA_NITROGEN
- MAGNESIUM
- model assumption checking plots
- partial effect plots
- contrast (subtract) inference plots
- by subtracting estimated response from 2 groups and comparing the confidence interval with 0, we can do inference (example - Temperature)
- In no-transplant group, our data suggest a significant increase in temperature in postive episodes than control (negative+baseline) episodes
- In transplant group, our data don’t suggest a significant increase in positive episodes than control (negative-baseline) episodes
Temp mean response
- Check model assumptions

- Partiel effect and contrast inference
***
Resp mean response
- Check model assumptions

- Partiel effect and contrast inference
***
Pulse mean response
- Check model assumptions

- Partiel effect and contrast inference
***
SBP mean response
- Check model assumptions

- Partiel effect and contrast inference
***
DBP mean response
- Check model assumptions

- Partiel effect and contrast inference
***
POTASSIUM mean response
- Check model assumptions

- Partiel effect and contrast inference
***
ALBUMIN mean response
- Check model assumptions

- Partiel effect and contrast inference
***
CALCIUM mean response
- Check model assumptions

- Partiel effect and contrast inference
***
SODIUM mean response
- Check model assumptions

- Partiel effect and contrast inference
***
WHITE_BLOOD_CELL_COUNT mean response
- Check model assumptions

- Partiel effect and contrast inference
***
PHOSPHORUS mean response
- Check model assumptions

- Partiel effect and contrast inference
***
PLATELET_COUNT mean response
- Check model assumptions

- Partiel effect and contrast inference
***
CO2 mean response
- Check model assumptions

- Partiel effect and contrast inference
***
PCO2 mean response
- Check model assumptions

- Partiel effect and contrast inference
***
CHLORIDE mean response
- Check model assumptions

- Partiel effect and contrast inference
***
BLOOD_UREA_NITROGEN mean response
- Check model assumptions

- Partiel effect and contrast inference
***
MAGNESIUM mean response
- Check model assumptions

- Partiel effect and contrast inference
